Methods, Systems, and Products for Classifying Subscribers

ABSTRACT

Methods, systems, and products classify subscribers based on viewing habits. An event record is stored that associates a command entered by a subscriber to a time. The event record is merged with data describing media programming to form event timeline data describing the at least one command and the media programming selected by the subscriber over a period of time. Credit card purchasing data is retrieved that describes the subscriber&#39;s credit card purchases. The event timeline data is compared to the credit card purchasing data. The subscriber is classified in a category associated with a product or service when the event timeline data indicates that the subscriber viewed an advertisement and afterwards purchased the product or service.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.12/247,246, filed Oct. 8, 2008, and now issued as U.S. Pat. No. ______,which itself is a continuation of U.S. application Ser. No. 10/016,988,filed Dec. 14, 2001, and now issued as U.S. Pat. No. 7,444,658, withboth applications incorporated herein by reference in their entirety.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialwhich is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in the United States Patent andTrademark Office patent file or records, but otherwise reserves allcopyright rights whatsoever.

FIELD OF THE INVENTION

The invention relates to a system and method for targeting content sentto a user.

BACKGROUND

Brand recognition achieved through advertisements is important to manybusinesses. As a result, consumers are often overwhelmed by the volumeof advertisements seen on television, in magazines, on the globalcomputer network (commonly referred to as the “Internet”), and othermedia venues.

Capturing the attention of consumers amid the clutter of otheradvertisements is of great importance to businesses seeking to promote abrand. Easily remembered slogans have been used in television, radio,and magazine advertisements for many years. Many memorable commercialshave gained recognition in popular culture for their lasting impressionson consumers.

In order for an advertisement to be valuable, however, it is not enoughthat consumers recognize the brand. A successful advertisement shouldincrease actual sales of the product. If a product's market comprisesonly a small number of consumers, an advertisement is of very littlevalue if it is not viewed by the relatively small group of consumers whopurchase the product. For example, an advertisement for denture adhesiveis only valuable if it is viewed by consumers who wear dentures orpurchase denture adhesive for family members. In addition, advertisementtime is used very inefficiently if an advertisement for a product usedby a small set of consumers is viewed by a large number of consumers.Although showing the advertisement to a large group of consumer mayreach the smaller group who may actually purchase the product, theadvertisement time is wasted on the consumers who are unlikely topurchase the product.

One method for reaching consumers who are likely to purchase a productwhile minimizing the wasted exposure to consumers who are unlikely topurchase a product is to place an advertisement in a media that thetargeted customers are likely to be viewing. Information regardingconsumer groups is collected and analyzed using numerous methods. Thisinformation is then used to predict consumer habits in a targeted group.For example, a company selling denture adhesive could determine that themajority of its customers are over age sixty-five. An advertisingconsultant might advise such a company that consumers over agesixty-five are likely to watch television shows including professionalgolf. Based on this information, the company selling denture adhesiveconcentrates its advertisements during professional golf tournaments.Decisions regarding when and where to place an advertisement may be evenless scientific. For example, numerous commercials for automobiles andautomobile accessories typically are placed during stock car racesbecause advertisers assume that stock car race enthusiasts also enjoypurchasing and modifying automobiles. Similarly, advertisements forchildren's toys are placed in children's television shows.

Although placing advertisements in a particular television show targetsconsumers who are likely to watch the show, such targeting is not aprecise approach. The viewers of any particular show may not be ahomogeneous group. For example, certainly not all viewers ofprofessional golf tournaments wear dentures. Even in a well-understooddemographic audience, many of the viewers of the show will be unlikelyto purchase the product.

In addition, recent technological advances have diminished the value ofadvertisements shown in the middle of a television show. With the wideavailability of video cassette recorders (“VCRs”) and digital videorecords (“DVRs”), viewers record television shows and may “fast-forward”the tape through the commercials. Television remote controls also allowviewers to watch other channels during commercials and then return tothe television show.

One response to the diminished value of advertisements shown in themiddle of television shows is commonly referred to as “productplacement.” Product placement involves placing a particular productdirectly in a television show or movie. Brand recognition is attainedwhen viewers see a favorite actor drinking a particular brand of softdrink.

Another technological advance in advertisements involves super-imposingan image into the television program. This technique is especiallycommon in sporting events, and allows numerous ads to be placed in thesame location. In the past, advertisers purchased a space for anadvertisement strategically placed in the sporting event space, forexample, behind home plate in a baseball game. The advertisement wouldbe highly visible to viewers watching the game on television. Morerecently, several advertisers may purchase the space behind home platein a baseball game. The advertisement is superimposed into the videofeed such that the advertisement is seen by viewers. The advertisementmay be changed at any point during the broadcast.

Efforts have also been made to target advertisements to consumers on theInternet. Various mechanisms are used to record the viewing habits of auser at a particular user terminal. The content of the pages viewed isanalyzed to determine what topics are of interest to a user.Advertisement are placed on the pages viewed by the user based on theseparticular topics of interest. These advertisements are often placedaround the primary text or image in a web page and are commonly referredto as “banner ads.”

Although the Internet environment enables advertisements targetedspecifically for an individual user, rather than a general demographicexpected in viewers of a specific television show, targetedadvertisements in the Internet environment have proven to be ineffectivefor capturing a viewers attention. Viewers are typically interested inthe information on the web page and ignore the banner advertisements.

Advertisements on television, including product placements, aregenerally effective for capturing a viewer's attention. However, suchadvertisements are typically displayed to a disproportionately largenumber of viewers who are unlikely to purchase the product. Targetedadvertisements on the Internet have the advantage of being displayed toconsumers who have demonstrated some interest in the relevant product.However, advertisements displayed on the Internet have proven relativelyineffective in capturing the attention of an audience. A consumer usingthe Internet easily ignores Internet advertisements.

These and other problems are avoided and numerous advantages areprovided by the methods and systems of the present invention.

SUMMARY OF THE INVENTION

The present invention comprises methods and systems for targetingadvertisements. In one embodiment, the method involves defining a matchbetween a user classification for characterizing a user and the user'sbehavior and an advertisement. A system collects user data about a userassociated with a user terminal such as a television, set top box, orcomputer terminal. The user data includes data from a plurality ofsources. Examples of data sources include information about purchasesmade by the user such as records of the products purchased, prices paid,and the time of purchases (“sales data”), information about mediaviewing habits of the user, information about demographics, and otherinformation describing the user. The system then classifies the user ina user classification and transmits media content to the user terminal.Examples of user classifications include classifications based oninterests such as sports, music, or comedy, classifications based onproducts or brands that a user purchases, and classifications based ondemographics such as marital and family status, income level, or gender.The media content includes video. The system inserts an advertisementinto the media content if a match is defined between the userclassification and the advertisement. The advertisement is one that isof interest to the users in the user classification.

In another embodiment, the system differentiates between two or moreusers who use the same user terminal. The system receives a useridentification to determine which user is viewing the media. The systemdefines a match between a user classification and an advertisement. Thesystem then classifies the user in a user classification and transmitsmedia content to the user terminal. The system inserts an advertisementinto the media content if a match is defined between the userclassification and the advertisement. Therefore, the systemdifferentiates between a plurality of users who view media content fromthe same terminal at different times.

In still another embodiment, the user data further includes sales dataof the user. A system detects the relationship between the sales dataand the user viewing selections. Examples of sales data includeinformation regarding credit card purchases, online purchases, andpurchases of other retail products. Sales data may include the pricespaid for products and the time that the purchase was made by the user.The user is classified in a user classification if a relationship isdetected between the user sales data and user viewing selections. In oneembodiment, a relationship between the sales data and user viewingselections is detected if the user views advertisements for a productand then purchases the product.

In yet another embodiment, the user is classified in a userclassification if the user data satisfies a predefined parameter.

In still another embodiment, the step of inserting the advertisementincludes embedding the advertisement into media content. For example, aproduct placed in a television show may be switched with a differentbrand.

In various embodiments, the user data includes global computer networkviewing data, survey data, or sales data. In other embodiments, theadvertisement includes an image embedded into media content, a videoprogram or a banner.

Systems and methods according to the present invention provide for theintegration of information about a user from multiple sources.Relationships between these sources are detected. For example, arelationship between the sales data of a user and the viewing selectionsof a user may be detected by a system, and the user classified based onthe relationship. Therefore, a system can detect if a user purchasesproducts for which advertisements have been viewed. Systems and methodsaccording to the present invention also enable embedding anadvertisement into media content transmitted to the user. Thus,different product placement advertisements in a television show may betransmitted to different viewers in a viewing system.

Advertisers will pay more for advertisements that are targeted for aspecific viewing audience. In addition, the same advertisement slot maybe sold to multiple advertisers. For example, a television show in whicha character holds a soft drink container could be shown to one usershowing one brand of soft drink while another user may see a secondbrand of soft drink. Because both brands are paying for theadvertisement space, a larger amount of revenue may be collected.

These and other advantages will become apparent to those of ordinaryskill in the art with reference to the detailed description anddrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an exemplary network for transmitting mediacontent to users.

FIG. 2 is a block diagram of an exemplary network for collecting datafrom a plurality of sources.

FIG. 3 is a block diagram of user data according to the presentinvention.

FIG. 4 shows an embodiment of a method according to the presentinvention.

FIG. 5 shows another alternative embodiment of a method according to thepresent invention.

FIG. 6 shows a block diagram of an embodiment according to the presentinvention.

FIG. 7 shows yet another alternative embodiment of a method according tothe present invention.

DETAILED DESCRIPTION

According to the present invention, advertisements are selectively sentto user terminals based on a user classification. According to anembodiment of the present invention, a system defines matches betweenuser classifications and an advertisement. Data is collected from aplurality of sources, which may be cross referenced to determinerelationships, for example, between user actions and viewing selections.A system classifies a user, defines matches between an advertisement anda user classifications, transmits media content to a user terminal, andinserts the advertisement into the media content if a match has beendefined between the user classification and the advertisementclassification.

FIG. 1 is a block diagram of an exemplary network for transmitting mediacontent to users. The media content is transmitted from a broadcaststation 19 to users at user terminals 21 a-21 n. The broadcast station19 may be a television airwave broadcast station or cable broadcaststation or other device for broadcasting media content in a mediadelivery network. In the embodiment shown in FIG. 1, the broadcaststation 19 comprises a cable television broadcast station. The mediacontent is generally in the form of video content, but may also includetext, video games, and audio content. The media content includesadvertisements, which may be in the form of video, a superimposed image,or an advertisement framing other content commonly referred to as a“banner.” Banner advertisement may be used, for example, to appear atthe same time as an electronic program guide. The media content may betransmitted by cable connections, satellite broadcast, or air wavebroadcasts to user terminals 21 a-21 n.

Users at user terminals 21 a-21 n select broadcast media content fromthe user terminals 21 a-21 n. User terminals 21 a-21 n may include anynetwork media device for receiving media content, including videodisplay terminals, set-top boxes (often called set-top terminals, cableconverters or home communications terminals), televisions, radios orpersonal computers connectable to the Internet or other media devicesfor communicating with a media delivery network. In the example shown,user terminals 21 a-21 n are television sets having a set-top box. Userterminals 21 a-21 n include a user interface for receiving user viewingcommands. User terminals 21 a-21 n send the user viewing selections tothe broadcast terminal 19, for example, using the methods and systemsdisclosed in (Attorney Docket No. 36968/265386 (BS01341), filedherewith), entitled “System and Method for Utilizing Television ViewingPatterns,” (Attorney Docket No. 36968/265389 (BS01378), filed herewith),entitled “System and Method for Developing Tailored Television ContentRelated Packages,” (Attorney Docket No. 36968/265387 (BS01342), filedherewith), entitled “System and Method for Identifying DesirableSubscribers.”

The broadcast terminal 19 is in communication with a server 11. In theexample shown, the broadcast terminal 19 is in communication with theserver 11 through a conventional cable television delivery network. Theserver 11 includes a central processor 14 for controlling and processingvarious computer functions, an operating system 18 for running softwareapplications, and system memory 16 for storing information. The server11 also includes a classification module 13 for classifying users andsending instructions to the broadcast station 19. The server 11 alsoincludes advertisement data 15 and user data 17 stored in the systemmemory 16.

When a user makes a viewing selection at a user terminal 21 a-21 n, theviewing selections are transmitted to the broadcast station 19 and theserver 11. Examples of viewing selections include when a user iswatching media content and what media content the user is watchingincluding the channels watched, the programs viewed from the channelswatched, and the time that the channel is watched. Viewing selectionsinclude how much of a particular television show or advertisement theuser watches. User data 17 is a database containing information about auser. The user data 17 is organized using conventional databasemanagement techniques. User data 17 includes user viewing selectionscollected by the user terminals 21 a-21 n, and other information, aswill become apparent from the following discussion. The advertisementdata 15 includes information about advertisements, such as identifyinginformation. For example, advertisements may be identified by theproduct featured, the times of day the advertisement is shown, thedemographic audience to which the advertisement is aimed and otherinformation about the advertisement. The advertisement data 15 may beuploaded to the system memory 16 by a system in communication with theserver 11 or entered into the system memory 16 through the server 11 bya computer operator. Example of advertisement data 15 includeinformation identifying an advertisement, descriptions of anadvertisement, and the times at which an advertisement is broadcast. Theadvertisements may be broadcast from the broadcast terminal 19. As wouldbe understood by one of ordinary skill in the art, alternative networkarrangement may be implemented. For example, the user terminals 21 a-21n may be connected to the server 11 directly rather than forming anindirect connection through the broadcast station 19.

FIG. 2 is a block diagram of an exemplary network for collecting datafrom a plurality of data sources. A data source is any source ofinformation and may include a database and/or a data collection device.Examples of data sources include records of retail purchases such ascredit card purchases and online purchases, records of user viewingselections, and records of user information such as demographicinformation. In addition to the configuration shown in FIG. 1, theserver 11 may be connected to a plurality of data sources as depicted inFIG. 2. Each data source contributes data to the user data 17 in thesystem memory 16. The classification module 13 reads and analyzes theuser data 17. Examples of data sources include shopping information 25,television habits 27, survey data 29, and computer viewing information31. Various configurations may be used to efficiently store and processthe user data 17. For example, information about a user may be collectedby a device and stored in a temporary memory location, such as a buffer,and uploaded to the user data 17 periodically. In another example,multiple servers or a network of computers may perform the function ofthe server 11.

Shopping information 25 includes information about the user's shoppinghabits. Shopping habits may be monitored through credit card purchaserecords or online electronic purchase records. Retail stores may keeprecords of purchases by using customer shopping cards in which customersare given discounts in exchange for using a shopping card. The shoppingcard is scanned every time a customer makes a purchase. Therefore, thecustomer and the customer's purchases are identified and recorded into adatabase regardless of whether the customer uses a credit card or debitcard for the purchase.

Television habits 27 include information about the user's viewinghabits. In one embodiment, a set top box may record television viewinghabits using methods and systems described in (Attorney Docket No.36968/265386 (BS01341), filed herewith), entitled “System and Method forUtilizing Television Viewing Patterns,” (Attorney Docket No.36968/265389 (BS01378), filed herewith), entitled “System and Method forDeveloping Tailored Television Content Related Packages,” (AttorneyDocket No. 36968/265387 (BS01342), filed herewith), entitled “System andMethod for Identifying Desirable Subscribers,” including shows andadvertisements viewed. The television habits 27 may include informationabout how much of a television show or advertisement was viewed, forexample, whether a user viewed an entire advertisement or only the firstfive seconds of the advertisement. In another embodiment, the usermanually keeps track of television shows that the user watches andrecords the television shows in a log.

Survey data 29 includes information collected by surveys about a user.Survey data 29 is collected by surveys, such as online surveys,telephone surveys, or mail-in surveys, and may include personalinformation about a user such as names, geographic locations, incomelevels and other demographic information.

Computer viewing information 31 includes information collected aboutwhat a user views on a computer. Examples of computer viewinginformation 31 include web pages viewed by the user on the Internet,Internet shopping purchases, topics of Internet searches, video gamesplayed, and other computer activities.

Information is collected from data sources such as shopping information25, television habits 27, survey data 29 and computer viewinginformation 31 to the system memory 16 and stored as user data 17. Inaddition, the classification module 13 analyzes the collectedinformation and stores the analysis in the user data 17.

FIG. 3 is a block diagram of user data according to the presentinvention. In the example depicted in FIG. 3, analyzed classificationsof user data 17 are shown. User data 17 includes information about oneor more users such as user 32, for example, in one or more data fields.The user data 17 includes raw data 30 about the user collected from thevarious data sources, such as the data sources depicted in FIG. 2.Referring back to FIG. 3, user 32 includes a user terminal address 31.The user terminal address 31 is an address for identifying the hardwareof a user terminal such as the user terminals 21 a-21 n as depicted inFIG. 1.

In the example depicted in FIG. 3, user 32 is classified into threeclassifications: a first user classification 33 entitled “sportsviewer,” a second user classification 35 entitled “stock car viewer,”and a third user classification 37 entitled “stock car viewer—model carbuyer.” The process by which the classification module 13 (FIG. 2) picksa classification is described in greater detail below. Each userclassification is associated with a set of parameters for determiningwhether a particular user should be classified in the userclassification. For example, the first user classification 33 entitled“sports viewer” may be defined as any user who watches more than anaverage of three hours of sports programming per week, the second userclassification 35 entitled “stock car viewer” may be defined as any userwho watches more than an average of two stock car races per month, andthe third user classification 37 entitled “stock car viewer—model carbuyer” may be defined as a user who watches more than an average of onestock car race per month and has purchased a model car within the lastyear.

In the example shown, the first user classification 33 entitled “sportsviewer” and the second user classification 35 entitled “stock carviewer” are defined by parameters based on the television habits 27 ofthe user as shown in FIG. 2. The third user classification 37 entitled“stock car viewer—model car buyer” is defined by parameters based on theshopping information 25 and the television habits 27 of the user asshown in FIG. 2. Any number of user classifications may be defined basedon data and information depicted in FIG. 2 such as shopping information25, television habits 27, survey data 29, computer viewing data 31 orany combination thereof.

FIG. 4 shows an embodiment of a method according to the presentinvention. More specifically, FIG. 4 shows a method for classifying auser performed by the server 11 and various components thereof (FIG. 2).The method starts at step 41. The server collects user data from datasources, such as the data sources depicted in FIG. 2 at step 43. Datafrom the data sources is transferred to a database such as user data 17in FIG. 2. The user data 17 is organized using conventional databasemanagement techniques. Referring back to FIG. 4, at step 45 theclassification module 13 (FIG. 2) includes a definition of a userclassification parameter. User classification parameters are definedcharacteristics that are used to classify a user. An example of a userclassification and corresponding classification parameter is a sportsfan with a classification parameter that requires a predefined level ofsports viewing. For example, if the classification parameter for asports fan is three hours of sports viewing per week, then a user willbe classified as a sports fan only if the user views at least threehours of sports per week. The user classification parameter may be adefined term in the classification module or defined by accepting inputfrom an operator as a variable into the classification module.

The classification module 13 compares the user data and the parametersat step 47. If the user data matches the parameter at step 47, the useris classified in the defined user classification at step 49. Theclassification module 13 records the classification as user data 17. Ifthe user data does not match the user parameter at step 47, then theclassification module 13 stops at step 51. The process depicted in FIG.4 may be repeated for many classifications and many users. Theclassification module 13 may classify a user into a plurality ofclassifications using the process depicted in FIG. 4. The variousclassifications are recorded as user data 17. For example, each user hasa data field in the user data 17 database for storing information aboutthe user, including the relevant user classifications. The userclassifications are used to determine which advertisements should besent to the user.

Example 1

In one illustrative example of the application of classification module13, the user views a stock car race every Saturday and Sunday afternoon,and the classification module analyzes the user data to determine if theuser should be classified as a “sports viewer.” In the example, the userclassification parameter for a sports viewer is a requirement that theuser view at least three hours of sports shows on average per week.

The classification module first examines whether the user is a sportsviewer beginning at step 41 in FIG. 4. The user data is collected atstep 43, which includes information that the user views a stock car raceevery Saturday and Sunday afternoons. The races average three and a halfhours each. The classification module determines that the user data,specifically, watching two three and a half hour races a week, matchesthe user classification parameter requirement that the user view atleast three hours of sports shows on average per week at step 47.Therefore, the user is classified as a sports viewer by theclassification module 13 at step 49 and the classification module stopsat step 51.

The classification module 13 then adds the classification “sports viewerto the user data in a configuration such as the user data 17 depicted inFIG. 3, which includes a first user classification 33 of “sportsviewer.” This information is valuable to an advertiser because the usermay be targeted for specific advertisements of particular interest tosports fans. Similarly, additional user classifications may be added tofurther refine the information, such as a user classification for “stockcar viewer.”

FIG. 5 shows another alternative embodiment of a method according to thepresent invention for correlating user data 17 from a plurality ofsources to classify a user. The user data 17 as shown in FIG. 2 includesinformation about the advertisements that a particular user viewed fromthe television habits 27 and products purchased from the shoppinginformation 25. Referring back to FIG. 5, the server 11 (FIG. 2) recordsadvertisements viewed at step 61 and products purchased at step 63. Atstep 65, the classification module compares the products purchased andthe advertisements viewed. For example, the advertisement is for aspecific product, and if the product purchased is the same as theproduct featured in the advertisement at step 65, then there is a matchbetween the products purchased and the advertisements viewed. Theclassification module 13 classifies the user as an advertisementviewer/purchaser for the particular product at step 67 and stops at step69.

Example 2

In an illustrative example for correlating user data 17 from a pluralityof sources to classify a user, referring to FIG. 2, the user data 17collects television habits 27 through the server 11 which indicate thatthe user has viewed ten advertisements for Brand A soft drinks andtwenty advertisements for Brand B soft drinks in one month. The userdata 17 collects shopping information 25 from the user's grocery storeshopping records indicating that the user buys two liters of Brand Bsoft drinks twice a month.

Referring back to FIG. 5, the server records advertisements viewed,specifically, ten advertisements for Brand A and twenty advertisementsfor Brand B at step 61. The server collects products purchased,specifically, two liters of Brand B soft drinks twice a month, at step63. At step 65, the classification module examines whether the productspurchased are the same as the advertisements viewed. Because the userviews advertisements for Brand B and buys Brand B, the user isclassified as a Brand B advertisement viewer/purchaser at step 67. Theuser is not classified with respect to Brand A because the user does notbuy Brand A. The classification module stops at step 69.

The classification of a user as an advertisement viewer/purchaser isvaluable to purchasers and sellers of advertisement. The user may betargeted for specific advertisements based on the classification and theuser's subsequent purchasing habits could be monitored. For example,based on Example 2, Brand A could decide to deliver more advertisementsto the user and monitor the user's shopping information to determine ifthe user switches brands. On the other hand, if a user watches manyadvertisements for a product and never purchases the product, the usermay not be receptive of the advertisements. Based on this information,people who market the product may decide to stop sending advertisementsto a user who never purchases the product despite viewing advertisementsbecause such advertising does not appear to influence the user. Productspurchased and advertisements viewed may be included as a userclassification parameter, for example, in the method depicted in FIG. 4.A predefined level of advertisements watched or products purchased maybe required for a user to be classified. For example, the userclassification parameter may be a requirement that the user view adefined number of advertisements and purchase a defined amount of theproduct.

FIG. 6 shows a block diagram of an embodiment according to the presentinvention for matching a user classification with a particularadvertisement, referred to herein as “matching definitions.” Thematching definitions are located in the system memory 16 on the server11 shown in FIG. 2 and are used by the classification module to sendinstructions for sending incentive, for example, to the broadcaststation 19. In the example shown, a first user classification 71 ismatched to a first advertisement 77. A second user classification 73 ismatched to a first advertisement 77, a second advertisement 79, and athird advertisement 81. A third user classification 75 is matched to athird advertisement 81. The matches are used to define whichadvertisements are transmitted to which viewers. Therefore, all users,such as the user 17 depicted in FIG. 3, having a first userclassification 71 are shown the first advertisement 77. All users havingthe second user classification 73 are shown the first advertisement 77,the second advertisement 79, and the third advertisement 81. All usershaving the third classification 75 are shown the third advertisement 81.

Example 3

In an illustrative example of an embodiment of the advertisement matchesdepicted in FIG. 6, the first advertisement 77 is an advertisement for astock car die cast model, the second advertisement 79 is for a serviceto purchase sports tickets, and the third advertisement 81 is forfootball memorabilia. The first user classification 71 is called a stockcar racing fan, for example having a user parameter requiring that theuser watch an average of one race per week. The first userclassification 71 is matched to the first advertisement 77 for a stockcar die cast model because a stock car die cast model is probably ofinterest to a stock car race fan. The second user classification 73 iscalled an ultra sports fan, for example, having a user parameterrequiring that the user watch at least three different sports programsevery week. The second user classification 73 is matched to the firstadvertisement 77 for a stock car die cast model, the secondadvertisement 79 for the ticket purchasing service, and the thirdadvertisement for football memorabilia because the second userclassification 73 has a general interest in sports and all threeadvertisements are probably of interest. The third user classification75 is called a football fan, for example, having a user parameterrequiring that the user watch an average of two football games permonth. The third user classification 75 is matched to the thirdadvertisement 81 for football memorabilia, which is probably of interestto a football fan. Any number of classifications and advertisementmatches may be made. For example, the second advertisement 79 for ticketpurchasing services, may be of interest to the first, second, and thirduser classifications, 71, 73, and 75, and therefore, the matchingdefinitions may be changed to map the first, second, and third userclassifications, 71, 73, and 75 to the second advertisement 79.

FIG. 7 shows another embodiment of a method according to the presentinvention. The classification module 13 as depicted in FIG. 1 sendstransmission instructions to the broadcast station 19. As discussedabove, the server 11 includes user data 17 and advertisement data 15.The advertisement data 15 includes information identifying one or morespecific advertisement. The classification module 13 includes matchingdefinitions, such as the matching definitions depicted in FIG. 6. Userclassifications are matched to one or more advertisements. In oneembodiment, the user to which the broadcast is sent is identified by theaddress of the user terminal, such as one of the user terminals 21 a-21n. The user terminal address 31 is depicted in FIG. 3 and is a componentof the user data 17. In another embodiment, a user at one of the userterminals 21 a-21 n in FIG. 1 may be prompted at the user terminal 21a-21 n to input a user identification, such as a code or password.Therefore, the system identifies the user by a code such that multipleusers at the same user terminal may be distinguished.

Referring again to FIG. 7, the classification module begins at step 91.The classification module 13 reads the user classifications assigned toa particular user terminal stored as user data 17 at step 93, such asuser classifications 33, 35 and 37 as depicted in FIG. 3. Theclassification module 13 determines whether there is a match definedbetween the user classifications and a particular advertisement at step95 using matching definitions such as the matching definitions depictedin FIG. 6. If there are no matches defined between a user classificationassigned to a particular user and advertisements, the classificationmodule 13 stops at step 99. If there is a defined match, theclassification module 13 sends instructions to the broadcast terminal totransmit the advertisement to the user at step 97.

In the embodiment shown in FIG. 1, the broadcast station 19 transmitsthe advertisements to the user terminal 21 a-21 n by overriding defaultadvertisements. The broadcast from the broadcast station 19 typicallyincludes default advertisements. The instructions to transmit theadvertisement to the user may include instructions to override defaultadvertisements in the broadcast media with advertisements for which amatch has been determined. If a user classification is matched to morethan one advertisement, the matched advertisements are transmitted tothe user at different times and more than one default advertisement maybe overridden.

Example 4

In one illustrative example for transmitting advertisements to a user, afirst user and a second user use the same user terminal, specificallyuser terminals 21 a in FIG. 1, for viewing television. The first andsecond users are assigned separate identification codes, which arerecorded in the system memory 16 for identifying the user. Theidentification codes may be assigned by a central administrator andcommunicated to the first and second users by electronic or mailmessages, or the first and second users may choose an identificationcode and enter it to the user terminal 21 a. The user terminal 21 asends the code to the system memory 16. The first user views a stock carrace every Saturday and Sunday afternoon, and the classification moduleanalyzes the user data as described in Example 1 to determine that thefirst user is classified as a “sports viewer.” In the example, the userclassification parameter for a sports viewer is a requirement that theuser view at least three hours of sports shows on average per week. Thesecond user watches nothing but cooking shows and has not been assigneda user classification.

An advertiser for a tennis shoe orders an advertisement to be sent toall “sports viewers” matching the defined classification. An operatoradds the information about the advertisement to the advertisement data15 in FIG. 1, including information identifying the advertisement. Theoperator also adds a match between the user classification “sportsviewer” and the tennis shoe advertisement. The media content thatcomprises the advertisement is transmitted to the broadcast station 19.

The first user turns on user terminal 21 a to watch the Saturday stockcar race. The user terminal 21 a prompts the first user for a useridentification code. Once the first user's identification code isreceived, the user terminal 21 a transmits the identification code tothe broadcast station 19 and the server 11. The user terminal 21 a alsotransmits the identification number of the user terminal 21 a to thebroadcast station 19 and the server 11. The user data collected, such asuser data 17 as depicted in FIG. 3, is therefore identified asassociated with the first user.

The classification module 11 in FIG. 1 has previously determined thatthe first user is classified as a “sports viewer” through a process suchas the process described in Example 1. The “sports viewer”classification is stored as a first user classification 33 in the userdata 17 as depicted in FIG. 3.

Referring to FIG. 7, the classification module begins at step 91. Theclassification module reads the user classifications assigned to thefirst user at user terminal 21 a at step 93. Specifically, theclassification module reads the “sports viewer” user classification. Theclassification module determines whether there is a match definedbetween the user classifications and a particular advertisement at step95. Because a match has been defined between the tennis shoeadvertisement and the “sports viewer” user classification, at step 97the classification module sends instructions to the broadcast terminalto transmit the advertisement to the user at step 97.

Referring back to FIG. 1, the broadcast terminal 19 receives theinstructions from the classification module 13 to transmit the tennisshoe advertisement to the user. The broadcast station 19 replaces adefault advertisement in the broadcast programming with the tennis shoeadvertisement.

If the second user identification were entered into the user terminal 21a, the classification module 13 would not detect a match between theuser classifications and the advertisements at step 95 in FIG. 7. Theclassification module would stop at step 99, and no instructions toreplace default advertisements in the broadcast programming would besent.

It will be apparent to those with skill in the art that there are manyalterations that may be made in the embodiments of the inventiondescribed above without departing from the spirit and scope of theinvention. For example, there are many ways that circuits and electronicelements may be combined to implement the method and system describedherein in various systems and hardware environments. The presentinvention may be implemented in various network environments, includingwireless and computer networks, or other networks supporting electronicdevices and the transmission of media content in television, radio,Internet or other network environments. There are similarly many waysthat independent programmers might provide software to provide thefunctionality associated with the present invention as taught hereinwithout departing from the spirit and scope of the invention. Havingthus generally described the invention, the same will become betterunderstood from the following claims in which it is set forth in anon-limiting manner.

1. A method, comprising: storing an event record associated with acommand; merging the event record with data describing media programmingto form event timeline data describing the command and the mediaprogramming selected by the subscriber over a period of time; retrievingsales data describing purchases; comparing the event timeline data tothe sales data; and associating the subscriber with a product or servicewhen the event timeline data indicates that an advertisement was viewedand afterwards the product or service was purchased.
 2. The method ofclaim 1, wherein retrieving the sales data comprises retrieving creditcard purchase records.
 3. The method of claim 1, wherein retrieving thesales data comprises retrieving online purchase records.
 4. The methodof claim 1, further comprising associating the product or service to atargeted advertisement.
 5. The method of claim 1, further comprisingassociating a subscriber to a targeted advertisement.
 6. The method ofclaim 5, further comprising sending the targeted advertisement to thesubscriber.
 7. The method of claim 5, further comprising sending thetargeted advertisement as a video to the subscriber.
 8. The method ofclaim 5, further comprising sending the targeted advertisement to thesubscriber as a banner in a web page.
 9. A system, comprising: aprocessor executing code stored in memory that causes the processor to:store an event record that associates a command entered by a subscriberto a time; merge the event record with data describing media programmingto form event timeline data describing the command and the mediaprogramming selected by the subscriber over a period of time; retrievesales data describing the subscriber's purchases; compare the eventtimeline data to the sales data; and associate the subscriber with aproduct or service when the event timeline data indicates that thesubscriber viewed an advertisement and afterwards purchased the productor service.
 10. The system according to claim 9, wherein the codefurther causes the processor to retrieve credit card purchase records.11. The system according to claim 9, wherein the code further causes theprocessor to retrieve online purchase records.
 12. The system accordingto claim 9, wherein the code further causes the processor to associatethe product or service to a targeted advertisement.
 13. The systemaccording to claim 9, wherein the code further causes the processor toassociate the subscriber to a targeted advertisement.
 14. The systemaccording to claim 13, wherein the code further causes the processor tosend the targeted advertisement to the subscriber.
 15. The systemaccording to claim 13, wherein the code further causes the processor tosend the targeted advertisement as a video to the subscriber.
 16. Thesystem according to claim 13, wherein the code further causes theprocessor to send the targeted advertisement to the subscriber as abanner in a web page.
 17. Computer readable memory storing processorexecutable instructions for performing a method, the method comprising:storing an event record that associates a command entered by asubscriber to a time; merging the event record with data describingmedia programming to form event timeline data describing the command andthe media programming selected by the subscriber over a period of time;retrieving sales data describing the subscriber's purchases; comparingthe event timeline data to the sales data; and associating thesubscriber with a product or service when the event timeline dataindicates that the subscriber viewed an advertisement and afterwardspurchased the product or service.
 18. The computer readable memoryaccording to claim 17, further comprising instructions for at least oneof i) retrieving credit card purchase records and ii) retrieving onlinepurchase records.
 19. The computer readable memory according to claim17, further comprising instructions for at least one of i) associatingthe product or service to a targeted advertisement and ii) associatingthe subscriber to a targeted advertisement.
 20. The computer readablememory according to claim 19, further comprising instructions for atleast one of i) sending the targeted advertisement to the subscriber,ii) sending the targeted advertisement as a video to the subscriber, andiii) sending the targeted advertisement to the subscriber as a banner ina web page.